PROJECT SUMMARY Optical imaging methods are well-established in neuroscience, but high-speed, high- resolution volumetric imaging of neural activity in deep tissue remains a challenge. A number of techniques address limited aspects of this goal, and most are applicable primarily to acute preparations. We propose to develop and test a novel approach to achieve three-dimensional ?deep-tissue? imaging for high spatial and temporal resolution neural recording by combining aspects of embedded optical probes with computational imaging techniques. Rather than use a single micro-endoscopic probe, we propose to utilize an array of narrower probes, or optrodes, to reduce the volume of tissue displacement. Computational imaging through each probe can be performed to achieve a field of view (FOV) at a desired distance from the probe tip. Combining the fields of view from multiple probes arranged in an array then provides a composite image field that is much larger than achievable from a single micro-endoscope. In our approach, each ?0.1 mm diameter probe of the array acts as an independent micro- endoscope. In order to achieve full-field imaging across the array, the individual fields must intersect, and the computational method must be scaled to accommodate, and stitch, multiple fields. In pursuit of these goals, we propose three Aims: Optimizing the FOV of a single micro-endoscope - The purpose of this Aim is to characterize the FOV for an individual probe at multiple depths, and optimize the FOV to about 0.3mm through control over the shape of the probe tip and light collection numerical aperture. Accelerating calibration and reconstruction - In this Aim, we will pursue efficient computational approaches for calibration based upon ray-tracing simulations and image reconstruction based on deep learning. Scaling the FOV with an endoscope array - The computational image reconstruction method will be scaled to accommodate small micro-endoscope arrays (e.g. 4 element) arranged in a hexagonal lattice with FOV of 0.6mm at a 1.5mm depth.